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Comparison of Signal-Analysis Techniques for Seismic Detection System for High-Speed Train Data: Effect of Bridge
1Railroad Structure Research Team, Korea Railroad Research Institute, Uiwang 16105, Korea.
Sensors (Basel, Switzerland)
|December 2, 2020
Summary
This study developed an earthquake warning system for high-speed trains using onboard accelerometers. The Wigner-Ville Distribution method showed the best performance for detecting seismic events, despite higher computational costs.
Area of Science:
- Geophysics and Seismology
- Railway Engineering
- Signal Processing
Background:
- Traditional earthquake warning systems rely on expensive seismometers.
- High-speed trains generate complex motion data that can interfere with seismic detection.
- Earthquake acceleration can be altered by the supporting bridge structures.
Purpose of the Study:
- To evaluate an earthquake warning system for high-speed trains utilizing onboard accelerometers.
- To develop a data analysis system for synthesized onboard datasets.
- To compare signal processing methods for seismic event detection in a train environment.
Main Methods:
- Synthesized virtual onboard datasets incorporating train acceleration and earthquake data.
- Included earthquake responses of bridges in virtual dataset synthesis.
- Compared Short-Time Fourier Transform (STFT), Wavelet Transform (WT), and Wigner-Ville Distribution (WVD) for data analysis.
Main Results:
- The Wigner-Ville Distribution (WVD) demonstrated superior detection performance for seismic events.
- Onboard accelerometers successfully measured both train and earthquake accelerations.
- The synthesized data accurately represented complex environmental interactions.
Conclusions:
- An earthquake warning system using onboard accelerometers is feasible for high-speed trains.
- WVD is the most effective signal processing technique for this application.
- Further research may focus on optimizing WVD for reduced computational cost.
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